Sensors may be used to generate sensor data indicative of objects in an environment. However, the raw form of the sensor data generated by the sensor may render it difficult to use or analyze the data. Thus, the sensor data may be segmented to transform it into a more useful form (e.g., identifying distinct objects in the data, areas in sensor data that are drivable (i.e., can be driven on), etc.). Segmenting the data generally involves partitioning or organizing the sensor data into a more meaningful or organized form so that, for example, areas of captured data in the sensor data may be identified or categorized. Data segmentation may be performed manually by a human. However, manual segmentation may be prohibitively time consuming and costly, often rendering it unsuitable for many applications. Image data may be automatically segmented using a computer, which partitions the image into different segments to provide a more meaningful or usable representation of the images. For example, an image may be segmented to uniquely identify objects within the image, which may be useful in some applications, such as, for example, operation of an autonomous vehicle. However, it may be difficult to automatically segment sensor data obtained from other types of sensors. In such instances, manual segmentation by humans may be necessary, rendering sensor data obtained from such sensor types prohibitively costly or difficult to use for some applications.